The teacher observes a 30x30 occupancy map of the environment where walls and object types (boxes, ramps, hiders, seekers) are encoded using different channels. The teacher observation is then processed through a feed-forward IMPALA conv-net [1]}. The teacher action specifies the \(x\)  and \(y\)  grid location of objects such as agents, boxes and ramps. All locations are sampled simultaneously using a factorized distribution. If the grid location specified by the teacher would cause a collision with a wall or object we change the location to a nearby location that avoids the collision.
